Hortonworks Apache-Hadoop-Developer : Hadoop 2.0 Certification exam for Pig and Hive Developer
- Exam Code: Apache-Hadoop-Developer
- Exam Name: Hadoop 2.0 Certification exam for Pig and Hive Developer
- Updated: Oct 05, 2026
- Q & A: 110 Questions and Answers
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Hortonworks Apache-Hadoop-Developer Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Transformation with Pig | - Pig Latin programming
|
| Data Ingestion | - Import data into Hadoop
|
| Data Analysis with Hive | - Hive query development
|
| Data Processing | - End-to-end Hadoop workflows
|
Hortonworks Hadoop 2.0 Certification exam for Pig and Hive Developer Sample Questions:
Which one of the following statements describes a Hive user-defined aggregate function?
- A. Operates on a single input row and produces a table as output
- B. Operates on a single input row and produces a single row as output
- C. Operates on multiple input rows and creates a single row as output
- D. Operates on multiple input rows and produces a table as output
Correct Answer: C 🗳️
Which of the following tool was designed to import data from a relational database into HDFS?
- A. Ambari
- B. HCatalog
- C. Flume
- D. Sqoop
Correct Answer: D 🗳️
Examine the following Hive statements:
Assuming the statements above execute successfully, which one of the following statements is true?
- A. The contents of File1 are parsed as comma-delimited rows and stored in a database
- B. Hive reformats File1 into a structure that Hive can access and moves into to/user/joe/x/
- C. The file named File1 is moved to to/user/joe/x/
- D. The contents of File1 are parsed as comma-delimited rows and loaded into /user/joe/x/
Correct Answer: C 🗳️
Which describes how a client reads a file from HDFS?
- A. The client contacts the NameNode for the block location(s). The NameNode contacts the DataNode that holds the requested data block. Data is transferred from the DataNode to the NameNode, and then from the NameNode to the client.
- B. The client contacts the NameNode for the block location(s). The NameNode then queries the DataNodes for block locations. The DataNodes respond to the NameNode, and the NameNode redirects the client to the DataNode that holds the requested data block(s). The client then reads the data directly off the DataNode.
- C. The client queries the NameNode for the block location(s). The NameNode returns the block location(s) to the client. The client reads the data directory off the DataNode(s).
- D. The client queries all DataNodes in parallel. The DataNode that contains the requested data responds directly to the client. The client reads the data directly off the DataNode.
Correct Answer: C 🗳️
Explanation: Only visible for Free4Torrent members. You can sign-up / login (it's free).
You want to count the number of occurrences for each unique word in the supplied input data. You've decided to implement this by having your mapper tokenize each word and emit a literal value 1, and then have your reducer increment a counter for each literal 1 it
receives. After successful implementing this, it occurs to you that you could optimize this by specifying a combiner. Will you be able to reuse your existing Reduces as your combiner in this case and why or why not?
- A. No, because the Reducer and Combiner are separate interfaces.
- B. Yes, because the sum operation is both associative and commutative and the input and output types to the reduce method match.
- C. No, because the Combiner is incompatible with a mapper which doesn't use the same data type for both the key and value.
- D. Yes, because Java is a polymorphic object-oriented language and thus reducer code can be reused as a combiner.
- E. No, because the sum operation in the reducer is incompatible with the operation of a Combiner.
Correct Answer: B 🗳️
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